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Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model
Citation:
Ran, L., Q. He, E. COOTER, AND V. Benson. Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model. Chapter 36, Douw G. Steyn & Silvia Trini Castelli (ed.), NATO/ITM Air Pollution Modeling and its Applications XXI. Springer Netherlands, , Netherlands, Series C:213-219, (2010).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Atmospheric ammonia (NH3) plays an important role in fine-mode aerosol formation. Accurate estimates of ammonia from both human and natural emissions can reduce uncertainties in air quality modeling. The majority of ammonia anthropogenic emissions come from the agricultural practices, such as animal operations and fertilizer applications. The current emission estimates at the U.S. Environmental Protection Agency (U.S. EPA) are based on the annual National Emission Inventory (NEI). However, accurate estimation of ammonia emissions in space and time has been a challenge. For instance, fertilizer applications vary in the date of application and amount by crop types and geographical area. With the support of the U.S EPA, we have responded by an agricultural fertilizer modeling system for use with a newly developed ammonia bi-directional flux algorithm in the Community Multiscale Air Quality (CMAQ) model. This modeling system will simulate NH3 emissions from fertilizer applications on agricultural lands rather than from emission estimates based on pre-defined emission factors. The goal for this paper is to demonstrate how this agricultural fertilizer modeling system is developed for a continental U.S. CMAQ l2-km modeling domain and the tools we developed in this system.